Grow your business faster with machine learning: Part I

Marketers are increasingly turning to Google’s machine learning to meet consumer expectations and grow their business, faster. To learn more, read the first post in our three-part blog series on machine learning.Read the post.

As more consumers come online around the world, there’s more opportunity than ever for marketers to reach potential customers beyond your borders. In fact, research shows that customers aren’t concerned about where a business is based as long as they’re happy with the product or service. For example, 96% of people didn't know that Booking.com is from the Netherlands, and of these, 90% said this wouldn't affect the likelihood of their buying from the company again.1

There are many tools and resources for businesses looking to expand. For example, Market Finder is a powerful tool built with insights from Google Search to prioritize the best markets for your business based on search volumes in your category, ease of doing business, consumer purchasing power, and more. It’s available in the US, UK, and China, with more countries on the way in 2018. Another resource is Consumer Barometer, which helps advertisers learn about consumer preferences and trends. Did you know that clothing, books, cosmetics, and computer hardware/software are the products most often purchased online from abroad?2 Last but not least, tap into the Go Global Community for the latest research on emerging market trends, conversations with international market specialists, and updates on new ads innovations. Companies from around the world have grown their businesses with these tools. For example:

Kabam is a leading provider of mobile games, including Marvel Contest of Champions with over 130M downloads. To expand its game into Japan, Hong Kong, and Taiwan, Kabam used insights from consumer gaming trends and video engagement from each market to localize its Search and YouTube campaigns. As a result, the game reached top 10 in download charts for its category on both iOS and Android in target APAC markets.

French DIY website ManoMano offers two million products from 750 sellers, including electrical, hardware, furniture and tools. The DIY market is highly seasonal and constantly changing -- customers love gardening and outdoor activities in warm seasons and indoor projects during the winter. ManoMano predicted these purchase patterns, understood consumer trends in each market, and engaged customers with timely, localized campaigns. As a result, its sales more than doubled in 2016, and ManoMano now has nearly 2 million customers across Europe, with localized websites in Belgium, France, Germany, Italy, Spain, and the UK.

It’s more important than ever for businesses, large and small, to think beyond borders with our Guide to Expanding Internationally. It’s a small world, after all.
Posted by Jay Bowden, Industry Director1. UK Google Consumer Surveys, 2014
2. The Consumer Barometer Survey 2014/15

Google is often the first stop for sports fans, music lovers, and theater goers looking for tickets and information about upcoming events, shows and concerts. We strive to connect these folks with relevant and accurate results, and are committed to delivering the best possible user experience.

Many venues sell tickets directly and some use resellers to help, making it easy to get the seats you want. Unfortunately, some ticket resellers provide limited transparency in their ads about ticket costs and fees, as well as their association with a specific venue or event. Lack of transparency can erode trust in the online ticket ecosystem and makes it harder for legitimate businesses to reach customers.

We only want companies that offer a great user experience on our platform. Effective today, we are tightening our standards and will require all event ticket resellers to be certified and to radically increase their transparency. This will give users more clarity on the vendor reselling the tickets and the total cost of those tickets, including any associated fees.

Provide the total and breakup of the price across fees and taxes before requiring payment information

Prominently provide the face value of the tickets being sold in the same currency (this will be required starting in March 2018)

This updated policy is a result of our own research as well as the insights and feedback we gathered from users, advertisers, partners and third-party industry groups. To allow advertisers time to prepare for this change, we issued a change to our AdWords policy page in November 2017.

According to Charlotte St. Martin, president of The Broadway League, “Google’s dramatic step in consumer protection is of major significance to The League’s membership. We strongly support requiring brokers who advertise Broadway tickets on its platform to disclose when they are unaffiliated with an official box-office and itemize costs before collecting payment.”

Transparency, trust and safety for our users will always be top priorities for Google. We remain dedicated to ensuring that the ads our users see are helpful, relevant and trustworthy.
Posted by David Graff, Senior Director, Trust & Safety, Global Product Policy

Consumers are more empowered than ever before and expect brands to provide fast and helpful experiences. That’s why leading marketers are 50% more likely to increase investments in capabilities like machine learning to help them win.1 In fact, brands like Rappi and AutoGravity are already using machine learning in AdWords to reach their most valuable app users and grow their businesses. In our final installment of this series, we explore how machine learning is being applied to bid optimization to help businesses make sense of the data around them and get better results at scale.

It’s more than a bid

The days of predictable web sessions are over, replaced by bursts of digital activity throughout the day on multiple devices. Your bids now have to take into consideration a wide range of contextual signals that impact ad performance, including a user’s device, location and time of day. That’s where machine learning can help.

AdWords Smart Bidding uses Google’s machine learning to help you set the right bid for every auction through three core capabilities:

Auction-time bidding: Smart Bidding sets bids for each individual auction, not just a few times per day. AdWords Smart Bidding evaluates the relevant contextual signals present at each of those auctions—such as time of day, specific ad creative being shown, or user’s device, and browser—to identify the conversion opportunity, and set an optimized bid tailored to each auction. This allows Smart Bidding to set millions of bids per second, something even an army of marketers wouldn’t be able to do.

Cross-signal analysis: Smart Bidding understands how signal combinations impact conversion rate. For example, a retailer might notice their mobile conversion rates are 20% higher than their desktop conversion rates, and set a mobile bid adjustment of +20%. However, this doesn’t account for the times of day where mobile conversion rates are even stronger, like in the mornings, when people are researching during their commute. Smart Bidding analyzes billions of these types of signals to identify meaningful correlations, and calculates bids based on how likely a conversion will occur.

Query-level learning: Smart Bidding maximizes performance for new and low-volume keywords. By looking at performance data across similar auctions in your account, Google’s machine learning platform makes informed bidding decisions and helps reduce performance fluctuations even when data is scarce. For example, let’s say you just added a new keyword “cheap flights to NYC.” If that query was already matching to another part of your account and similar auctions, Smart Bidding simply applies what it’s learned about that query to set the best possible bid.

Focus on the next big opportunity

Brands around the world are using Smart Bidding to unlock growth for their business and reinvesting their time and money into new opportunities.

Harmoney, a peer-to-peer lending service in New Zealand, teamed up with its agency, First Digital, to find more, qualified applicants while still hitting an aggressive ROAS goal. They used Target ROAS across their non-brand Search campaigns to reach customers who were most likely to apply and be approved for a personal loan. As a result, Harmoney saw a 219% growth in high-value accounts at a 37% lower cost-per-acquisition (CPA). Importantly, Smart Bidding freed up 5 hours per week for the team to focus on high-value tasks like testing ad copy and learning more about their best customers.

FirstPoint is a Swiss-based digital agency that wanted to maximize its client’s Search budget while driving more conversions. After testing Smart Bidding, the agency moved away from manual bidding in favor of Maximize conversions. It increased conversions by 2.4x, increased conversion rates by 12%, and decreased CPA by 59%.

Put machine learning to the test

Moving to Smart Bidding and enabling machine learning to do the heavy lifting for you doesn’t have to happen overnight. Set up a campaign draft and experiment to run a 50/50 split test and see how your old bidding strategy stacks up against one powered by Google’s machine learning. With a little time, you may find yourself delivering better results. For our own media team at Google, Smart Bidding is now a best practice and is enabled across 98% of eligible campaigns.

Check out our updated Smart Bidding guide for best practices on picking the right bid strategy for your business goals.

Last week at the Consumer Electronics Show, we learned about today’s more empowered consumer. They're more curious, demanding and impatient than ever before, and expect assistive experiences everywhere–like checking in and unlocking their hotel room using their smartphone.

Meeting these rising consumer expectations is critical. Over the next two weeks, we’ll explore some of our favorite AdWords products and show how machine learning is enabling brands to meet those expectations, while saving time and improving performance.

Applying machine learning in AdWords

Campaign management involves time-consuming tasks. Rather than manually adding thousands of keywords or individually testing headlines to see which ones work best, you can train Google’s machine learning platform to do it for you.

For example, you might’ve had new products added to your inventory or more content added to your website recently. Dynamic Search Ads would see this and automatically fill gaps in keyword coverage to help you reach people who are searching for those new products and services.

Or to show relevant ads that fit anywhere across the millions of sites in the Google Display Network, you can upload more creative assets to your Smart display campaign and automatically show relevant ads to the right people. Machine learning makes all of this possible.

Changing the app game

For app developers and marketers, we know competition is fierce: the number of developers with more than 1 million monthly installs grew by 35% year over year.1 There are more apps and experiences competing for your users’ attention and dollars than ever before. This is another area where machine learning is changing the game.

Universal App campaigns (UAC) enable brands like Rappi, a delivery service in Latin America, to reach their most valuable users across Google Play, Search, Display Network, and YouTube with a single campaign.

Rappi uploaded as many creative assets as it had, allowing Google’s machine learning platform to rotate each asset, understand which ones perform best across each channel, and show the ads that users are most likely to engage with. After only one month, Rappi’s conversion rates grew by 10X, and the brand expanded into Brazil, Mexico and Argentina.

AutoGravity, an auto financing company, reached tens of thousands of car buyers and increased user engagement by 120% in only 5 weeks. The brand plans on increasing UAC investment by 200% to reach more of its highest-value users, people who are most likely to receive credit ‘approval’.

How does UAC reach these types of high-value users? Google’s machine learning platform uses insights from Google.com and Google Play, web data and other signals, in addition to information about your app. This data is analyzed across each channel where AdWords shows your ads and is updated in real time. That’s how AdWords can quickly pick up on trending keywords, like events and holidays, and ensure your ads show to the right users.

AdWords then looks at people who have completed your selected action, like ‘approvals’, and those who haven’t, as well as user signals that are unique to each auction. Device type, operating system, network, apps they already have, and other signals create patterns that help identify high-value users. These patterns are used to predict future auctions, where and how to bid, and what ads to show and to whom.

Using machine learning, brands are not only delivering better performance at scale, but they’re also unlocking their most precious resource: time.

Paul Teresi, Growth Executive at Skyscanner, a travel app, says he’s been able to save a lot more time thanks to UAC. “Now, I can focus on truly understanding our users, metrics, and discovering growth and expansion opportunities necessary to keep us ahead of the curve.”

To learn more about how Universal App campaigns can help you reach your most valuable users, take our new education course.

Next week, we’ll conclude our journey with a look at how machine learning is being applied to bid optimization, including an interesting case study from Google’s in-house media team.

Posted by David Mitby, Director of Product Management1. Google Internal Data, May 2017

Today, we’re launching a new interactive education program for Universal App campaigns (UAC). UAC makes it easy for you to reach users and grow your app business at scale. It uses Google’s machine learning technology to help find the customers that matter most to you, based on your business goals—across Google Play, Google.com, YouTube and the millions of sites and apps in the Display Network.

UAC is a shift in the way you market your mobile apps, so we designed the program’s first course to help you learn how to get the best results from UAC. Here are a few reasons we encourage you take the course:

Learn from industry experts. The course was created by marketers who’ve been in your shoes and vetted by the team who built the Universal App campaign.

Learn on your schedule. Watch snackable videos at your own pace. The course is made up of short 3-minute videos to help you master the content faster.

Practice what you learn. Complete interactive activities based on real life scenarios like using UAC to help launch a new app or release an update for your app.

So, take the course today and let us know what you think. You can also read more about UAC best practices here and here.

There’s no denying 2017 was a difficult year, with several issues affecting our community and our advertising partners. We are passionate about protecting our users, advertisers and creators and making sure YouTube is not a place that can be co-opted by bad actors. While we took several steps last year to protect advertisers from inappropriate content, we know we need to do more to ensure that their ads run alongside content that reflects their values. As we mentioned in December, we needed a fresh approach to advertising on YouTube. Today, we are announcing three significant changes.

Stricter criteria for monetization on YouTube

After careful consideration and extended conversations with advertisers and creators, we’re making big changes to the process that determines which channels can run ads on YouTube. Previously, channels had to reach 10,000 total views to be eligible for the YouTube Partner Program (YPP). It’s been clear over the last few months that we need the right requirements and better signals to identify the channels that have earned the right to run ads. Instead of basing acceptance purely on views, we want to take channel size, audience engagement, and creator behavior into consideration to determine eligibility for ads.

That’s why starting today, new channels will need to have 1,000 subscribers and 4,000 hours of watch time within the past 12 months to be eligible for ads. We will begin enforcing these new requirements for existing channels in YPP beginning February 20th, 2018.

Of course, size alone is not enough to determine whether a channel is suitable for advertising. We will closely monitor signals like community strikes, spam, and other abuse flags to ensure they comply with our policies. Both new and existing YPP channels will be automatically evaluated under this strict criteria and if we find a channel repeatedly or egregiously violates our community guidelines, we will remove that channel from YPP. As always, if the account has been issued three community guidelines strikes, we will remove that user’s accounts and channels from YouTube.

This combination of hard-to-game user signals and improved abuse indicators will help us reward the creators who make engaging content while preventing bad actors and spammers from gaming the system in order to monetize unsuitable content. While this new approach will affect a significant number of channels eligible to run ads, the creators who will remain part of YPP represent more than 95% of YouTube's reach for advertisers.

Those of you who want more details, can find additional information in our Help Center.

Manually reviewing Google Preferred

We’re changing Google Preferred so that it not only offers the most popular content on YouTube, but also the most vetted. We created Google Preferred to surface YouTube's most engaging channels and to help our customers easily reach our most passionate audiences. Moving forward, the channels included in Google Preferred will be manually reviewed and ads will only run on videos that have been verified to meet our ad-friendly guidelines. We expect to complete manual reviews of Google Preferred channels and videos by mid-February in the U.S. and by the end of March in all other markets where Google Preferred is offered.

Greater transparency and simpler controls over where ads appear

We know advertisers want simpler and more transparent controls. In the coming months, we will introduce a three-tier suitability system that allows advertisers to reflect their view of appropriate placements for their brand, while understanding potential reach trade offs.

We also know we need to offer advertisers transparency regarding where their ads run. We’ve begun working with trusted vendors to provide third-party brand safety reporting on YouTube. We're currently in a beta with Integral Ad Science (IAS) and we're planning to launch a beta with DoubleVerify soon. We are also exploring partnerships with OpenSlate, comScore and Moat and look forward to scaling our third-party measurement offerings over the course of the year.

The challenges we faced in 2017 have helped us make tough but necessary changes in 2018.
These changes will help us better fulfill the promise YouTube holds for advertisers: the chance to reach over 1.5 billion people around the world who are truly engaged with content they love. We value the partnership and patience of all our advertisers to date and look forward to strengthening those ties throughout 2018.

At the start of the new year, we take time to look at what’s ahead, from eating healthier to spending more time outdoors. This week at the Consumer Electronics Show, we get to take a similar look ahead, at the future of technology. Thanks to innovations like smartphones and voice-activated speakers, consumers are now super-empowered and expect more from their favorite brands. This is redefining the consumer experience and reshaping what’s required of marketers.

To help you meet rising consumer expectations, over the next three weeks we’ll share insights and best practices from brands that have made machine learning an enabler for new opportunities in this “age of assistance”–instead of another challenge to figure out.

Solving problems with machine learning

At its core, machine learning is a new way of problem solving. Rather than spending hundreds of hours manually coding computers to answer specific questions, we can save time by teaching them to learn on their own. To do that, we give the computer examples until it starts to learn from them–identifying patterns, like the difference between a cat and a dog.

To illustrate how machine learning can help solve some of the most complex problems in the world, take the latest advances in medicine. In the US, doctors know survival rates for skin cancer increase dramatically with early detection.1 That’s why researchers at Stanford University used Google’s machine learning platform, TensorFlow, to train a model that can identify cancerous skin conditions from healthy ones with 91% accuracy–on par with 21 board-certified physicians.

New opportunities to accelerate growth

As marketers, you don’t wake up everyday expecting to save lives. But we do ask ourselves a very different question: how can I grow my business faster? This is where Google’s machine learning technology can help.

We know that choosing where your ads show and manually adjusting bids is time consuming, leaving less time for strategic tasks, like capturing the latest trends or entering new markets. Google's machine learning considers billions of consumer data points everyday, from color and tone preference on mobile screens, to purchase history, device and location. With products like Universal App Campaigns and Smart Bidding, it’s now possible to use this data to help deliver millions of ads customized for your customers, and set the right bid for each of those ads–in real time.

Even if you’re not using these AdWords innovations, you’re still seeing the benefits of machine learning. Google uses information about search queries, historical ad performance and other contextual signals combined with machine learning, to predict whether or not someone will click on your ad. This predicted click-through rate helps determine the selection, ranking and pricing of your ads–meaning machine learning is already working to show the right ads to the right customers.

Over the next three weeks, we’ll continue exploring how you can use machine learning to reach your marketing goals and grow your business faster. To get the latest updates on this series, follow along on the Inside AdWords blog or subscribe to our Best Practices newsletter.

With 2018 only weeks away, our team compiled a few AdWords New Year’s resolutions for you to consider.

1. I will try out new AdWords innovations.
The new AdWords experience is packed with new features like promotion extensions and ad variations that have helped advertisers improve performance. For example, Torrid saw a 30% lift in conversion rate when using promotion extensions to highlight limited time offers alongside ad copy that emphasized quality and fit. Merkle also increased conversions by 14% after running an ad variations test with expanded text ads. And new shortcuts like pressing “G” then “T” let you navigate to any page within your account so you can get to the data that matters to you, faster.

As you search in AdWords, keyboard shortcuts will be suggested for future use.

2. I will test more.
Testing in AdWords is crucial when optimizing your account. To increase return on ad spend (ROAS), the Honest Company used campaign drafts and experiments for efficiently exploring new strategies—saving 50% more time compared to manual trials. The Honest Company experimented with sending shoppers to product pages versus special offer landing pages for "bath" and "body" keywords. As a result of the test, the Honest Company saw a 47% increase in ROAS when sending shoppers to unique offer landing pages.

3. I will do more in less time.
Smart Bidding helps marketers bid both more efficiently and effectively. Powered by Google’s machine learning, it automatically sets the right bid for each and every auction. Bonprix, a leading fashion brand in Europe, drove 25% more revenue at the same ROAS and more than 50% in incremental revenue on mobile, by using Smart Bidding with Target ROAS. According to Sönke Harms, Bonprix’s Head of Shopping ads, Smart Bidding allowed the team to focus on “delivering key analyses, identifying strategic opportunities, and driving important initiatives.” Read our best practices guide to get started with Smart Bidding.

4. I will reach more shoppers.
Mobile searches for “where to buy” grew more than 85% over the past two years.1 That’s why it’s critical to help shoppers find your business both online and when they’re on-the-go. With location extensions, you can show your address, business hours, a map to your location, and more. You can also reach and bid higher specifically for people who are located near your business. Jerome’s Furniture combined location extensions with local inventory ads and store visits measurement to increase conversions by 93% across online and offline channels.

Location extensions show your business information in various formats on the Search Network, Display Network, and Google Maps.

5. I will stay informed.
With the AdWords app, you can receive timely alerts notifying you of issues and opportunities in your account. You can also easily pause campaigns and adjust budgets and bids. Adding, editing, and removing keywords is also simple. Best of all, you can do all of this right from the palm of your hand. Download the app now on Android or iOS.

With the AdWords app, you can manage your keywords and more on-the-go.

To receive more AdWords tips and tricks, be sure to subscribe to our Best Practices newsletter.

From our AdWords family to yours—happy holidays, and we’ll see you in 2018!

Would it surprise you to hear that we see 34% more shopping searches on Christmas Day than on Black Friday1? That’s just one of the eye-opening consumer trends we’re watching closely now that the 2017 holiday season is in full swing.

With mobile, shoppers know they can easily find and get what they’re looking for up until the last minute. So, despite all of the improvements retailers have made to shipping speed and product availability, many people still wait to buy. That means that a lot of December’s holiday shopping happens right before—and even after—Christmas, giving more reason for retailers to continue to drive store traffic from online and offline media throughout the season.

Early birds they are not

Retailers may be pushing their holiday deals earlier and earlier, but some shoppers are still waiting longer and longer, weighing their options to make their final choices.

When shoppers consider a new purchase, they spend 13 days on average shopping for the item. But once they decide to buy, almost half expect it either the same day or the next day2. In fact, mobile searches related to “same day shipping” have grown 120% since 20153.

It’s no wonder, then, that we see online conversions from the week before December’s shipping cutoff date on par with the the week of Cyber Monday4, as holiday shoppers make a last-ditch effort to get their presents sent to their doorstep.

Once shipping cutoff hits, last-minute shoppers make a mad dash

The last week before Christmas is crazy busy, of course, but it's also very local. Around Dec. 21, when the online shipping cutoff passes, shoppers increasingly turn to their hometown stores to get what they need.

Regardless of which day of the week Christmas falls, the in-store holiday rush starts on the Friday one full week before Christmas. The Saturday after that is typically the second-busiest day of December. The busiest day of all in the last month of the year? That’s Dec. 23, regardless of what day of the week it falls on5.

Searches for “where to buy” peak on Dec. 23 as last-minute shoppers grab their final gifts and stocking stuffers. Some popular examples: “where to buy Cards Against Humanity?”, “where to buy Yeti Cups?", and even “where to buy coal?”6

‘Where to buy’ searches in 2016

Meanwhile, mobile searches for “open now” and “store hours” grow through December and peak on Christmas Day. That includes searches like, “what stores are open near me on Christmas?”, “what grocery stores are open on Christmas?” and “what stores are open right now?"7

This year, retailers have an edge: With Christmas on a Monday, there are two full weekends (Dec. 15-17 and 22-24) in the 10 days before the holiday. This bodes well for store traffic with shoppers out in force on Fridays and Saturdays.

The takeaway? With people turning to stores at the last minute, be sure to highlight your local products for the best chance at drawing shoppers to your door. Check out our Shopping best practices guide to learn how you can drive traffic to your store this holiday season.

Christmas may be over, but the shopping isn't

The days between Christmas and New Year's Eve are just as busy as every other day in December (other than Christmas week itself). For general shopping queries (such as “shopping near me” or “store hours”), we see 34% more searches on Christmas Day than we do on Black Friday. Though searches for “where to buy” increase up until Dec. 23, the queries recover to pre-Christmas week levels and stay steady for the final week of the year8.

And this post-Christmas shopping busyness isn’t just happening online. In fact, last year we saw about 20% of all December store traffic happen in the six days after Christmas9. And why is that? With searches for “clearance” spiking on December 2610, shoppers are likely looking to redeem gift cards, make returns and exchanges, find gifts for people they haven’t seen yet, or decide to “gift” themselves a little extra.

While Black Friday is still a major in-store shopping day for some categories, such as electronics and furniture, many specialty stores see more foot traffic leading up to, and after, Christmas Day than on Black Friday. In 2016, toy stores and bookstores, for example, saw the most foot traffic of the holiday season on Dec. 23, while video game stores saw their busiest holiday shopping day on Dec. 2611.

Mobile has fundamentally changed the way holiday shoppers complete their lists. They expect to be able to find what they want, when they want it. And that means holiday shopping is happening right before—and even after—Christmas. That's a big opportunity for marketers who keep the lights on even after Santa slides through.

Since we introduced product ratings, we’ve been working on new ways to help you gather feedback about your products and drive more qualified traffic to your site. Today, we’re making product ratings available in all markets where Google Shopping is present.

Product ratings appear in the form of stars and review counts on Shopping ads. This 5-star rating system represents aggregated review data for the product, compiled from multiple sources including merchants, third-party aggregators, editorial sites and users.

How to enable product ratings on Shopping ads

If you have a Merchant Center account for your store, you’ve already taken the first step towards displaying Product Ratings. Once you sign up and satisfy the program requirements, you can begin uploading Product Ratings feeds to your Merchant Center account. Alternatively, you may want to work with one of our approved third-party aggregators.

Additionally, you can now collect reviews about the products you sell through Google Customer Reviews. Whenever your shoppers complete a purchase, we’ll ask them about their shopping experience with your store, as well as the product they purchased. The reviews collected about their shopping experience will contribute to your seller rating and, the product reviews collected can make you eligible to show product ratings. To learn more about how to use Google Customer Reviews to collect product reviews, see here.

Learn More

The product rating program is now available globally. For more information, please visit our Help Center.